The CIL Development Team will be attending the ToScA (Tomography for Scientific Advancement) Conference, held at Queen Mary University of London, 7-9th September 2022.

We will be running a workshop, and giving a talk.

Workshop: Practical X-ray CT reconstruction with the CCPi Core Imaging Library (CIL)

7th September (times TBC)

In this course we will be covering the basics of X-Ray CT acquisition and reconstruction. We will introduce the filtered back projection (FBP) algorithm and the cone beam variant (FDK), which are the most widely used algorithms for reconstruction of XCT data. We will discuss the family of iterative reconstruction algorithms with regularisation that can be employed when FBP/FDK do not lead to satisfactory results. The course will make use of the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging, developed by the Collaborative Computational Project in Tomographic Imaging (CCPi) and available from https://www.ccpi.ac.uk/cil.

The course will make use of an online platform where all the relevant software and data is pre-installed, but details on how to install CIL will be provided. CIL provides FBP/FDK, state-of-the-art iterative reconstruction algorithms, pre-processing and visualization tools as well as readers for some of the common micro-CT data formats.

In this three-hour hands-on training course you will:

• learn to load in and process micro-CT data (e.g. Nikon and Zeiss).
• produce and display your very own reconstructions using CIL.
• appreciate the pros and cons of iterative reconstruction when compared to filtered back-projection.
• experiment with different iterative reconstruction algorithms.
• get an overview of CIL and how to get started.

Talk: Advanced CT reconstruction with the CCPi Core Imaging Library (CIL)

8th or 9th September (time TBC)

We present the Core Imaging Library (CIL) – a versatile open-source Python package for tomographic imaging reconstruction and analysis. CIL can be used for the entire tomography data workflow from loading common lab and synchrotron X-ray CT data formats, pre-processing for various imperfections, reconstruction by filtered back-projection or a variety of iterative methods as well as data visualisation and exploration. CIL offers tools for conventional as well as challenging setups including in-situ experiments with imaging rigs, fast dynamic CT, hyper-spectral CT, and non-standard scan geometries such as laminography. In this talk, we give an overview of the functionality provided by CIL and provide multiple application examples, including comparisons of filtered back-projection reconstruction with emerging iterative reconstruction methods. CIL is developed by the Collaborative Computational Project in Tomographic Imaging and is available from https://www.ccpi.ac.uk/CIL.